Skip to main content
OpenTrials
Completed

NCT Number: NCT06605976

Evaluating the Impact of Ambient AI on Documentation Efficiency and Clinician Burnout in Primary Care Settings

This clinical trial aims to evaluate the effectiveness of an ambient listening AI product, DAX CoPilot, in improving clinical documentation efficiency and reducing clinician burnout in primary care settings. Researchers will compare results from a group who was given a license to use DAX CoPilot to a group who was not given a license. Participants in the DAX group will use DAX CoPilot system for EHR documentation and participants in the control group will use use standard EHR documentation methods. Participants will also be asked to complete surveys and assessments related to their views on technology and experiences of burnout.

Completed

Looking for future studies?

Notify Me

Key information

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Samaritan Health Services

Corvallis, Oregon, 97330, United States

About this study

This pilot study aims to evaluate the effectiveness of an ambient listening AI product in improving clinical documentation efficiency and patient satisfaction, reducing clinician burnout in primary care settings, and improving operational implementation strategies by harnessing end-user psychology. Employing a randomized, prospective design, the study involved 25 clinicians who were given an ambient listening AI product (DAX CoPilot) after a 1 month baseline period and asked to use it for clinical documentation with a focus on problem-focused visits over a 3-month period, with a control group of 20 clinicians continuing traditional documentation methods. The primary outcomes include changes in documentation efficiency (measured through metrics such as time spent on documentation per patient) and clinician burnout (assessed using the validated Mini-Z 2.0 burnout inventory). Secondary outcomes involve patient satisfaction with clinicians' use of the AI tool and examining end-user technology acceptance among clinicians using a survey based on the Unified Theory of Acceptance and Use of Technology (UTAUT). The study aims to provide insights into the potential of AI-assisted documentation tools in enhancing clinical workflow and addressing the growing concern of clinician burnout.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Licensed Clinicians: Independently licensed clinicians (MDs, DOs, NPs, PAs) who have been actively practicing at Samaritan Health Services for at least 6 months.
  • Primary Care Only: Providers must have a listed specialty of family medicine, internal medicine, or pediatrics, and currently practice primarily in a primary or urgent care clinic.
  • Provider has an Apple iPhone and is willing to install Epic Haiku.

Exclusion criteria

  • Inpatient-Only Clinicians: Exclude clinicians who only, or primarily, work in inpatient settings, as documentation needs and challenges may differ significantly from those in outpatient settings.
  • Trainees: Exclude medical students and residents due to their varying levels of experience and dependence on supervisory oversight.
  • Minimum Outpatient Encounters: Exclude clinicians with fewer than 100 outpatient encounters per month to focus on those with a significant workload in outpatient settings.
  • Android Smartphones Users: Clinicians may not use Android, or generally any non-Apple or non-iOS smartphones, given the software limitations of the selected intervention technology.
  • Corrective Action: Exclude clinicians facing dismissal, corrective, or disciplinary action.
  • Scheduled leave longer than 3 weeks during the study period

Treatment and study plan

DAX CoPilot Group

Behavioral

Participants in this group were given a license for DAX CoPilot and asked to use it for clinical documentation.

Primary outcomes

  1. Documentation efficiency

    Time frame: From baseline to the end of the 3 month experimental period

    Compare average documentation, workload, and InBasket metrics (tracked by Epic Signal and through a custom data pull for SHS) before and after the implementation of ambient AI among the intervention and control groups; time in notes per appointment, time in notes per scheduled day, progress note length, note composition, time outside scheduled hours, time outside of 7 AM to 7 PM, pajama time, visits closed same day, time in InBasket per appointment, InBasket message turnaround time

Secondary outcomes

  1. Burnout

    Time frame: From baseline to the end of the 3 month experimental period

    Clinician burnout as assessed using the Mini-Z 2.0 burnout inventory

Other outcomes

  1. Patient satisfaction

    Time frame: 3 months experimental period

    Patient satisfaction with the experience of the clinician using DAX CoPilot via a patient survey after a visit in which it was used

Sponsors and collaborators

Lead sponsor

Samaritan Health Services

Other

Registry information

Important dates

Study start
2024
Primary completion
2024
Study completion
2024
First posted
Sep 20, 2024
Registry last updated
Sep 20, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.